Triple
T23332577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STAR File syntax |
E591485
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | metadata representation language |
C1700
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: metadata representation language Context triple: [STAR File syntax, instanceOf, metadata representation language]
-
A.
Knowledge representation language
A knowledge representation language is a formal system used to encode information about the world in a structured, machine-interpretable way so that computers can reason about it.
-
B.
metadata standard
A metadata standard is a structured set of rules and definitions that specify how information about resources should be described, formatted, and shared to ensure consistency, interoperability, and discoverability.
-
C.
markup language
chosen
A markup language is a system for annotating text or data with tags that define its structure, presentation, or semantics, enabling consistent formatting and processing by software.
-
D.
data serialization language
A data serialization language is a formal notation used to structure, encode, and represent data so it can be stored or transmitted and later reconstructed consistently across different systems.
-
E.
Web ontology language
A web ontology language is a formal language designed for representing rich, machine-interpretable knowledge about concepts, relationships, and constraints on the web to enable automated reasoning and interoperability.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
Created at: April 17, 2026, 5:15 p.m.